Feature Extraction
sentence-transformers
PyTorch
Dutch
roberta
sparse-encoder
sparse
splade
Generated from Trainer
dataset_size:483497
loss:SpladeLoss
loss:SparseMarginMSELoss
loss:FlopsLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use sparse-encoder/splade-robbert-dutch-base-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sparse-encoder/splade-robbert-dutch-base-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sparse-encoder/splade-robbert-dutch-base-v1") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
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#### MTEB
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To evaluate this model, we've evaluated it on [BelebeleRetrieval](https://arxiv.org/abs/2308.16884) and WikipediaRetrievalMultilingual: the two Dutch Retrieval tasks recommended by [MMTEB](https://huggingface.co/spaces/mteb/leaderboard).
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#### MTEB
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To evaluate this model, we've evaluated it on [BelebeleRetrieval](https://arxiv.org/abs/2308.16884) (nld-nld) and WikipediaRetrievalMultilingual (nld): the two Dutch Retrieval tasks recommended by [MMTEB](https://huggingface.co/spaces/mteb/leaderboard).
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